# SwishrJobs

> An autonomous service agency. It executes small digital jobs in an
> isolated container and returns independently verified deliverables to
> other AI agents over HTTP, MCP, and A2A.

## Machine-readable surfaces

- A2A agent card (protocol 1.0): https://swishrjobs.com/.well-known/agent-card.json
- OpenAPI document: https://swishrjobs.com/openapi.json
- Capability list: https://swishrjobs.com/v1/capabilities
- Measured performance (success rate, latency, cost per result): https://swishrjobs.com/v1/performance
- Capability selection (rank by task, reliability, cost): https://swishrjobs.com/v1/select
- Job list: https://swishrjobs.com/v1/jobs
- Agent contract: https://swishrjobs.com/agents.md
- ARD manifest: https://swishrjobs.com/.well-known/ard.json
- AI Catalog: https://swishrjobs.com/.well-known/ai-catalog.json
- MCP tools (stdio): run `swishrjobs serve --mcp` (tools/list, tools/call)

## Capabilities

- boundary-value-generation: Produce a standard-library Python module that produces boundary values for an integer range, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need the boundary and just-outside values of an inclusive integer range, with tests.
  - Not for: Do not choose this for non-integer ranges, random data generation, or property-based testing frameworks.
  - Example requests: Write a Python module that produces the boundary and just-outside values for an integer range, with tests. | I need boundary values for an inclusive integer range for test data. | Generate a boundary-value module and prove it with pytest.
- csv-json-transformation: Produce a standard-library Python module that transforms CSV text into a JSON array of objects, plus pytest tests. The transformation is chosen from a registered template so the result is deterministic and verifiable. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need a tested, standard-library function that parses CSV text into a JSON array of objects, one per row.
  - Not for: Do not choose this for per-column type coercion or bespoke rules, or if you need the file converted for you rather than a module that does it: this delivers code, not converted data.
  - Example requests: Give me a Python module that turns CSV text into a JSON array of objects, with tests. | I have CSV and need JSON objects, one per row, produced by a tested function. | Convert CSV to JSON and prove it with a pytest suite.
- data-validation-module: Produce a standard-library Python module that validates a record and returns structured errors, plus pytest tests. The rule set is chosen from a registered template so the result is deterministic and verifiable. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when a record must be checked against a registered rule set and the result is a list of human-readable errors, with tests.
  - Not for: Do not choose this for rules outside the registered template, or when you need a schema-validation library rather than a self-contained module.
  - Example requests: Write a Python module that validates a record against a fixed rule set and returns a list of error strings. | I need a validation function that returns an empty list for valid input, with tests. | Generate a data-validation module and its pytest suite.
- dataset-quality-report: Produce a standard-library Python module that computes a quality report for an array of records, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need a computed quality summary of a record array: counts, presence, nulls, completeness ratio, exact duplicates.
  - Not for: Do not choose this for statistical or semantic quality (outliers, drift, schema conformance beyond the fixed checks).
  - Example requests: Write a Python module that reports record count, per-field presence and duplicate count for a dataset, with tests. | I need a data-quality summary: null counts, completeness ratio, exact duplicates. | Generate a dataset-quality report module and test it.
- duplicate-group-report: Produce a standard-library Python module that groups records sharing a key field, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need each repeated key value reported with its count and the positions of its members.
  - Not for: Do not choose this to remove duplicates (use record-deduplication) or to match near-duplicates.
  - Example requests: Write a Python module that groups records by a key field and reports duplicated values, with tests. | I need to know which key values occur more than once, with counts and positions. | Generate a duplicate-group report module and prove it with pytest.
- edge-case-check: Produce a standard-library Python module that reports boundary conditions for a text value, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when a text value must be classified against a fixed set of boundary conditions, one boolean each.
  - Not for: Do not choose this for validation with error messages (use data-validation-module) or for conditions outside the fixed set.
  - Example requests: Write a Python module that reports which boundary conditions a text value satisfies, with tests. | I need checks for empty, whitespace-only, over-length, non-ASCII and control characters. | Generate an edge-case check module and prove it with pytest.
- field-mapping: Produce a standard-library Python module that renames and selects JSON fields using a mapping, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when fields must be renamed and selected via an explicit source-to-destination mapping.
  - Not for: Do not choose this for computed or transformed values: only names and selection change.
  - Example requests: Write a Python module that renames and selects JSON fields using a mapping, with tests. | I need to rename keys in an object or array of objects via a source-to-destination map. | Generate a field-mapping module and test it.
- json-csv-conversion: Produce a standard-library Python module that renders a JSON array of objects as CSV text, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need a tested function that renders a JSON array of objects as CSV, using the union of keys as the header.
  - Not for: Do not choose this when you need the conversion performed on your data now, or when the CSV format must be bespoke (delimiter, quoting rules).
  - Example requests: Write a Python function that renders a JSON array of objects as CSV, with tests. | I need JSON to CSV with the header being the union of all keys. | Generate a JSON-to-CSV module and prove it with pytest.
- json-schema-inference: Produce a standard-library Python module that infers a JSON Schema from sample records, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need a draft 2020-12 JSON Schema inferred from sample objects, with keys present in every record marked required.
  - Not for: Do not choose this for a hand-tuned schema or for constraints the samples do not express (formats, ranges, enums).
  - Example requests: Write a Python module that infers a JSON Schema from sample records, with tests. | I need a JSON Schema generated from example objects, marking common keys as required. | Generate a schema-inference module and prove it with pytest.
- key-normalisation: Produce a standard-library Python module that rewrites JSON object keys to lower snake_case, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when object keys must become lower snake_case, with values left untouched.
  - Not for: Do not choose this expecting acronym splitting: a capital run like HTTPServer becomes httpserver, not http_server.
  - Example requests: Write a Python module that rewrites JSON object keys to lower snake_case, with tests. | I need camelCase keys converted to snake_case without changing the values. | Generate a key-normalisation module and a pytest suite.
- malformed-record-detection: Produce a standard-library Python module that reports records violating a fixed field contract, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need one entry per offending record, naming its index and the rule it broke, against a fixed contract.
  - Not for: Do not choose this for a contract outside the registered template, or if you need the records corrected rather than reported.
  - Example requests: Write a Python module that finds records violating a fixed field contract, with tests. | I need a checker that reports the index and failed rule for each bad record. | Generate a malformed-record detector and prove it with pytest.
- markdown-table-rendering: Produce a standard-library Python module that renders JSON records as a Markdown table, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when JSON records must become a GitHub-flavoured Markdown table with pipes escaped.
  - Not for: Do not choose this for HTML tables, spreadsheet formats, or column alignment rules beyond the template.
  - Example requests: Write a Python module that renders JSON records as a GitHub Markdown table, with tests. | I need a Markdown table renderer that escapes pipes so data cannot break the table. | Generate a Markdown-table module and test it.
- metadata-extraction: Produce a standard-library Python module that extracts key/value metadata from a document head, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when 'key: value' metadata must be read from the head of a text document, preserving duplicate keys rather than overwriting.
  - Not for: Do not choose this for YAML/TOML front matter parsing or for metadata spread through the body.
  - Example requests: Write a Python module that extracts 'key: value' metadata from a document head, with tests. | I need front-matter style metadata pulled out, recording duplicate keys. | Generate a metadata-extraction module and test it.
- nested-flattening: Produce a standard-library Python module that flattens a nested object into dotted-path keys, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when a nested object must become single-level dotted-path keys, leaving lists as leaves.
  - Not for: Do not choose this if you need lists indexed into keys (a.0, a.1) or a custom separator: the template fixes the behaviour.
  - Example requests: Write a Python module that flattens a nested object into dotted-path keys, with tests. | I need nested JSON flattened to single-level keys like a.b.c. | Generate a flattening module and prove it with pytest.
- python-multifile-package: Produce a small multi-module Python package from a registered, deterministic template: an implementation module, a public facade, a pytest suite, and a README. [intro $15.00 (provisional)] [available]
  - Use when: Choose this when the deliverable is a package rather than one file: a facade, an implementation module, a test suite, and a README, from a registered template.
  - Not for: Do not choose this for a single module (use python-utility-module) or for a package whose structure or behaviour is bespoke: only the registered template's shape is produced.
  - Example requests: Build a small Python package with an implementation module, a public facade, tests and a README. | I need a multi-file Python deliverable, not a single script. | Create a package where the facade re-exports the implementation and the tests import both.
- python-utility-module: Produce a small standard-library Python module from a registered, deterministic template, plus the pytest tests that verify it. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need one small, importable standard-library Python module whose behaviour matches a registered template, delivered with a passing pytest suite you can re-run yourself.
  - Not for: Do not choose this for a multi-file package (use python-multifile-package), for code needing third-party packages, or when you cannot name a registered template: the behaviour is fixed by the template and an unregistered request is rejected rather than guessed.
  - Example requests: Write me a small Python function that turns a title into a URL slug, with tests. | I need a pure-standard-library Python module with a docstring and a pytest suite. | Generate a Python helper module I can import, plus the tests that prove it works.
- readme-generation: Produce a standard-library Python module that generates a Markdown README from function signatures, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when a Markdown README must be produced from a list of function signatures, one section each.
  - Not for: Do not choose this for prose documentation or API references beyond signature-derived sections.
  - Example requests: Write a Python module that generates a Markdown README from function signatures, with tests. | I need a README generator that documents each supplied function signature. | Generate a README-generator module and prove it with pytest.
- record-deduplication: Produce a standard-library Python module that removes duplicate objects from a JSON array, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when duplicates must be removed from a JSON array, keeping the first occurrence and preserving order, optionally on a key subset.
  - Not for: Do not choose this for fuzzy matching or similarity-based deduplication: the comparison is exact.
  - Example requests: Write a Python module that removes duplicate objects from a JSON array, keeping the first, with tests. | I need deduplication by a key subset that preserves input order. | Generate a dedupe module and a pytest suite for it.
- regex-from-examples: Produce a standard-library Python module that builds a regular expression from positive and negative examples, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when a regular expression must be derived from examples using the shared literal prefix, correctly escaped.
  - Not for: Do not choose this expecting a general regex synthesiser: it uses the longest literal prefix shared by the positive examples, and negative examples are used for checking, not for general inference.
  - Example requests: Write a Python module that builds a regex from positive and negative examples, with tests. | I need a regular expression derived from example strings, escaped correctly. | Generate a regex-builder module and prove it with pytest.
- regression-suite-generation: Produce a standard-library Python module that turns recorded input/output pairs into a pytest module, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when recorded input/output pairs must become one deterministic pytest case per pair.
  - Not for: Do not choose this to test behaviour not covered by the recorded pairs, or to generate non-deterministic tests.
  - Example requests: Write a Python module that turns recorded input/output pairs into a pytest module, with tests. | I have input/output examples and want a deterministic regression test suite. | Generate a regression-suite generator and prove it with pytest.
- text-parser-module: Produce a standard-library Python module that parses a text format into a structured result, plus pytest tests including malformed input. The format is chosen from a registered template so the result is deterministic and independently verifiable. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need a standard-library parser for a registered text format, delivered with tests that include malformed input.
  - Not for: Do not choose this for a bespoke grammar the templates do not cover, or for formats needing a third-party parser library.
  - Example requests: Write a Python module that parses a key=value config file into a dict, with tests for malformed input. | I need a parser module that handles a fixed text format and rejects bad input with a clear error. | Generate a text-parsing module plus tests that cover the malformed cases.
- webhook-payload-validation: Produce a standard-library Python module that validates a webhook payload envelope, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when an incoming webhook envelope must be validated to the registered shape and rejected with structured errors.
  - Not for: Do not choose this for provider-specific signature verification or for a schema that differs from the registered envelope.
  - Example requests: Write a Python module that validates a webhook JSON envelope and returns structured errors, with tests. | I need to check a webhook has a non-empty event string, an object data, and an optional id. | Generate a webhook-validation module and its pytest suite.
- xml-json-conversion: Produce a standard-library Python module that converts an XML document into JSON, plus pytest tests. [intro $5.00 (provisional)] [available]
  - Use when: Choose this when you need a tested, standard-library XML-to-JSON conversion that keeps attributes as '@name' keys and collects repeated elements.
  - Not for: Do not choose this when the document uses DTDs, external entities, or namespaces: those are not resolved. It is also a code deliverable, not a conversion of your specific file.
  - Example requests: Write a Python module that converts an XML document into JSON, with tests. | I need XML to JSON where attributes become @name keys and repeated elements become lists. | Generate an XML-to-JSON converter and test it, including malformed XML.

## Choosing a capability

Match your task against a capability's summary and example requests. Each
capability also states what it is not for: read that before submitting, so a
request outside the fixed contract is not sent. Built-in capabilities are
produced by deterministic recipes, not by model inference, so the same inputs
always yield the same deliverable. A request outside a capability's registered
template is rejected rather than approximated.

## Job lifecycle

1. POST /v1/jobs to preflight and receive a quote.
2. POST /v1/jobs/{id}/authorize with the quote id and accepted amount to run.
3. GET /v1/jobs/{id} to read the result and its verification.

Send an Idempotency-Key header on authorize to make a retry safe.

Authorization returns an `access_token`. Reading a job (GET /v1/jobs/{id})
and listing jobs (GET /v1/jobs) require it, sent as the `X-Job-Token` header
or a `token` query parameter. Without it a job is reported as not found, and
the job list is empty: one customer cannot read another's job or artifacts.

## Honest status

- Execution gate: closed on this host.
- Payment: not configured on this build, so no money can be charged. Quotes and acceptances are recorded for audit only.
- All prices are provisional and unvalidated by a real buyer.
- No accounts and no API keys. A per-job access token, issued at
  authorization, is the only credential and it grants access to that one job.

## Source

- Repository: https://github.com/Mahmoudaly187/swishrjobs